Using autoresearch to optimise marketing campaigns under budget constraints
The post Let the AI Do the Experimenting appeared first on Towards Data Science.
Bytes Speak All Languages: Cross-Script Name Retrieval via Contrastive Learning
Why learn 8 scripts when you can learn 256 bytes?
The post Bytes Speak All Languages: Cross-Script Name Retrieval via Contrastive Learning appeared first on Towards Data Science.
The Essential Guide to Effectively Summarizing Massive Documents, Part 2
We have the document clusters, and it’s time to unlock their true potential! Let’s explore how to extract meaningful information from the actionable clusters.
The post The Essential Guide to Effectively Summarizing Massive Documents, Part 2 appeared first on Towards Data Science.
Introduction to Approximate Solution Methods for Reinforcement Learning
Learn about function approximation and the different choices for approximation functions
The post Introduction to Approximate Solution Methods for Reinforcement Learning appeared first on Towards Data Science.
How to Improve Claude Code Performance with Automated Testing
Learn how to get the most out of Claude Code
The post How to Improve Claude Code Performance with Automated Testing appeared first on Towards Data Science.
How to Select Variables Robustly in a Scoring Model
More variables don't make a better scoring model. Stable variables do. Here's how to find them.
The post How to Select Variables Robustly in a Scoring Model appeared first on Towards Data Science.
Correlation vs. Causation: Measuring True Impact with Propensity Score Matching
Learn how Propensity Score Matching uncovers true causality in observational data. By finding "statistical twins," we eliminate selection bias to reveal the real impact of your interventions and business decisions.
The post Correlation vs. Causation: Measuring True Impact with Propensity Score Match...
A short intro to scientific methodology to combat "prompt in, slop out"
The post Ivory Tower Notes: The Methodology appeared first on Towards Data Science.
Git UNDO : How to Rewrite Git History with Confidence
For any data scientist who works in a team, being able to undo Git actions can be a life saver. This practical guide will teach you all you need to know to save the day.
The post Git UNDO : How to Rewrite Git History with Confidence appeared first on Towards Data Science.
I Replaced GPT-4 with a Local SLM and My CI/CD Pipeline Stopped Failing
The hidden cost of probabilistic outputs in systems that demand reliability
The post I Replaced GPT-4 with a Local SLM and My CI/CD Pipeline Stopped Failing appeared first on Towards Data Science.
From Risk to Asset: Designing a Practical Data Strategy That Actually Works
How to turn data into a strategic asset that enables faster decisions, reduces uncertainty, and helps the organization move toward its goals.
The post From Risk to Asset: Designing a Practical Data Strategy That Actually Works appeared first on Towards Data Science.
Generating Minecraft Worlds with Vector Quantized Variational Autoencoders (VQ-VAE) and Transformers
The post Dreaming in Cubes appeared first on Towards Data Science.
Your RAG System Retrieves the Right Data — But Still Produces Wrong Answers. Here’s Why (and How to Fix It).
Your RAG system is retrieving the right documents with perfect scores — yet it still confidently returns the wrong answer.
I built a 220 MB local experiment that proves the hidden failure mode almost nobody talks about: conflicting context in the same retrieval window. Two contradictory documents co...
How to Learn Python for Data Science Fast in 2026 (Without Wasting Time)
What I wish I did at the beginning of my journey
The post How to Learn Python for Data Science Fast in 2026 (Without Wasting Time) appeared first on Towards Data Science.
6 Things I Learned Building LLMs From Scratch That No Tutorial Teaches You
From rank-stabilized scaling to quantization stability: A statistical and architectural deep dive into the optimizations powering modern Transformers.
The post 6 Things I Learned Building LLMs From Scratch That No Tutorial Teaches You appeared first on Towards Data Science.
What It Actually Takes to Run Code on 200M€ Supercomputer
Inside MareNostrum V: SLURM schedulers, fat-tree topologies, and scaling pipelines across 8,000 nodes in a 19th-century chapel
The post What It Actually Takes to Run Code on 200M€ Supercomputer appeared first on Towards Data Science.
Prefill Is Compute-Bound. Decode Is Memory-Bound. Why Your GPU Shouldn’t Do Both.
Inside disaggregated LLM inference — the architecture shift behind 2-4x cost reduction that most ML teams haven't adopted yet.
The post Prefill Is Compute-Bound. Decode Is Memory-Bound. Why Your GPU Shouldn’t Do Both. appeared first on Towards Data Science.